SUMMIT AT GLANCE

The Maintenance Analytics Summit is an annual event bringing together practitioners, experts, academia, and visionaries working with Data-Driven Maintenance to share ideas, and discuss ways to harness the full potential of machine data and Advanced Analytics to improve and automise their condition monitoring and maintenance processes. The agenda is suited to guide you through the process of extracting knowledge from data by using the latest methodologies, tools and algorithms. With domestic and international speakers on stage, interactive panel discussions and plenty of learning and networking activities in the exhibition area, the Maintenance Analytics Summit is the place to be for all professionals and organisations working with Data Management and utilisation of data, Analytics, IIOT, Data Science, and Machine Learning, to innovate and improve their operational processes ex. predict and avoid machine failure.

Tickets
120
22
Stages
2
Exhibitors
10
SCHEDULE

The program is tailor-made to follow a red thread and guide you through the entire process of setting up a Data - and AI-Driven Predictive Maintenance

  • 15 May
    day 1
  • PLENUM & ANALYTICS, MODELLING AND INNOVATION STAGE
  • DATA INTEGRATION AND CONTEXTUALISATION STAGE
07:40
Registration Starts
8:20
Chairman’s Opening remarks - The game changer - Analytics, IIOT, AI and Predictive Maintenance

Amer_Mohammed_Stena_Line
8:30
The Digital Butterfly Effect

Everyone is taking about digitalization and digital strategies. There is no “digital strategy”, there is only strategy! At Stena Line our mission statement is “The works first cognitive ferry operator”. I’ll show you how!

Key takeways:
- What to actually do when doing “digitalization”
- Using A.I as a foundation
- Changing the culture to understand machine learning


Amer Mohammed
Head of Digital Innovation
Stena Line

Amer Mohammed is an entrepreneur who has crashed three companies and sold two. Friends and colleagues told him that the shipping industry will never change at it will always be “old men on a boat”. Amer is proving them wrong and will show the world how.

Martin_Lundqvist_Government_Solutions
Rado_Kotorov_Information_Builders
Lennart-Christennsson-GE-Digital
9:00
Panel: The State of Now: Challenges with Data- and AI-Driven approach to Predictive Maintenance



Martin Lundqvist
VP Government Solutions
Arundo Analytics

Martin is a vice president at Arundo Analytics based in Stockholm. He is responsible for Arundo's work within Government Solutions internationally, and a Nordic sales executive. Before joining Arundo, Martin spent almost two decades as a management consultant at McKinsey & Company helping clients transform operational performance using technology across a variety of sectors. He can be seen by the piano or in front of Python code when he's not building something awesome in Minecraft with his 10-year-old son.

Rado Kotorov
CIO
Information Builders

Dr. Rado Kotorov works with both the business intelligence (BI) and the iWay product divisions to provide thought leadership, analyze market and technology trends, develop innovative product roadmaps, and create rich programs to drive adoption of BI, analytic, data integrity, and integration technologies. He strives to make BI and business analytics more accessible, intuitive, and collaborative through the adoption of innovative Web 2.0, advanced visualization, predictive modeling, search, and mobile technologies.

Lennart Christennsson
Global Leader Asset Performance Management/OEM
GE Digital

Leading the efforts to connect complex, industrial equipment/processes for OEMs and create business values through the GE Predix solution in the IIoT space such as Asset Performance Management, Field Service Management & Edge computing powered by Predix/ServiceMax.
Background as development leader/CTO in Automation Control/IT, Telecommunications and Intelligent cameras, last 10 years in sales

Jake_Bouma_Arundo_Analytics
09:30
Quick wins and dead ends: a collection of customer stories in asset-heavy industries

Is the application of machine learning to Predictive Maintenance different to what we initially thought? By reviewing real world successes and failures across diverse industrial applications, this talk will challenge current formulations, priorities and perceptions of value in Predictive Maintenance today.

Learning points:
- Showcase of real world use cases in asset-heavy industries
- Perspective on the feasibility and value of different Predictive Maintenance and related use cases
- How to take data science beyond prototypes and scale across the industrial organization

Jake Bouma
Data Scientist
Arundo Analytics

Jake is a data scientist at Arundo Analytics based in the Oslo office, where his recent focus has been on anomaly detection and machine learning diagnostics for Oil & Gas. Prior to joining Arundo, Jake has several years' experience in the telecommunication and railway transport sectors in South Africa. Jake holds a masters degree in nuclear physics from Katholieke Universiteit Leuven in Belgium and since academia has been feeding a passion for putting big data and data science into operation in a way that fundamentally changes organizations for the better.

speaker
10:00
Short Round Table discussions - How to start with Data Driven approach to Maintenance

10:30
Coffee and networking - Peer-to-Peer meetings
11:00
Providing Assurance on Diagnostics and Prognostics Technology

The adoption of diagnostics and prognostics technology is accelerating in different industries. Fundamentally diagnostics is a “health meter” describing the state of the fault, degradation, failure modes in question. Given the deployment of the technology in industrial and safety critical applications there is a need to develop legible approach proving the effectiveness of the technology

Learning points:

- Diagnostics and prognostic technologies are enablers of availability and safety
- Diagnostics acts as a “failure meter” employing sophisticated analytical techniques based on sensors and other information
- In reviewing diagnostics and prognostics, there is a need to decompose the architecture into different functional blocks
- A robust assurance framework will be necessary to provide comprehensible metrics that allow confidence and wider acceptance of the technology

Joseph Morelos
Strategic Market Manager, Technology Innovation
Lloyd’s Register

Joseph is a Technology Market Manager with Lloyd’s Register. Joseph has 15 years of engineering experience across the marine industry covering design, testing and review of engineering systems across different asset types from cruise ships to naval assets. Prior to joining the innovation team he dealt with cryogenic engineering, reviewing LNG applications including monitoring technologies

Peter_Loof_Health_Orsted
11:30
Adding RPA to your mix of models

Maintenance is a process of physical and digital events. Being able to predict the optimal timing is a leap in cost reduction - but only when you can perform the required sequence of events. Learn how Ørsted is adding Robotics Process Automation and how to increase your chance of a successful implementation.

Learning points:

- Think big. Have a clear vision of where you wish to go
- Start small and iterate often. Try it out and embrace your mistakes
- They are your best source for learning
- Design for success. Gain support by augmenting human capabilities rather than "compete to replace"

Peter Loof Helth
Head of the Robotics Excellence Centre
Ørsted

Peter Loof Helth is Head of Robotics Excellence Centre at Ørsted with responsibility for driving the strategic development and implementation of robotics. Over the past 12 months, Peter and his team has been successful in creating a stable, secure and scalable RPA architecture that mixes well with cognitive technologies. After spending more than 15 years in the energy industry, Peter has a deep insight in the complexities of an industry in fundamental change, and the curiosity and drive to identify opportunities and change things to the better through new methods. Peter and his team has delivered excellent results on a strategic and operational level in several areas including operations research, game theory, transfer pricing and real option valuation. An example of this, is the successful Gas release swap auction concept in 2006-2013. In addition to his extensive experience in mathematics and financial analysis Peter is former Captain in the Danish army reserves. Peter holds a M.Sc. in Operations Research from the University of Aarhus, Denmark.

Kieran_Notte_ServiceMax
12:00
The Road to Zero Unplanned Downtime

Keeping your assets running is mission critical for your reputation, customer satisfaction and for keeping costs low, but what is the true cost of unplanned downtime? In 2017, ServiceMax from GE Digital commissioned independent research firm Vanson Bourne to uncover the impact unplanned downtime can have on companies and field service management teams as well as how technology is helping companies to manage and maintain assets to prevent outage failures.

In this session Kieran Notter, Director of Global Customer Transformation will discuss the results from the ground-breaking research and provide examples of ServiceMax customers who are leading the way when it comes to predictive and preventive maintenance of mission critical assets. Is achieving zero unplanned downtime your number one priority? Join this session to discover why it should be.

Kieran Notter
Director of Global Customer Transformation
ServiceMax

Kieran is acknowledged as a service industry domain expert with 30 years’ experience. He specializes in field service revenue and working capital improvements, with a particular passion for supply chain operations. He is highly effective at partnering with customers to deliver tangible, practical results across their service operations. Having previously worked for companies including Kodak, Bell & Howell and most recently Pitney Bowes he understands the importance of a logical approach that is supported by real time analytics. His considerable experience in implementing and using systems such as SAP, Servigistics(PTC), Oracle (Siebel), Salesforce & ServiceMax enables him to recognise a client’s challenges and facilitate solutions that lead to sustainable growth. His recent consultancy engagements have delivered improvements such as reducing field service Inventory levels by 45% whilst maintaining a higher First Time Fix rate.

12:30
Networking Lunch
Ali_Rastegari_Volvo
13:30
Condition based maintenance in the manufacturing industry

Presenting frameworks and guidelines to support the development and implementation of condition based maintenance in manufacturing companies, exemplifying practical case studies such as vibration analysis of machine tool spindle units.

Learning points:
- The need for Condition Based Maintenance (CBM)
- Factors to evaluate CBM cost effectiveness
- A process of CBM implementation
- CBM of machine tools, focusing on the use of vibration monitoring technique to monitor the condition of machine tool spindle units

Ali Rastegari
Maintenance developer
Volvo GTO

Ali Rastegari is employed as a maintenance developer at Volvo Group Trucks Operation (GTO). He has been awarded the PhD degree in Innovation and Design from Mälardalen University in 1 December 2017. He has been an industrial PhD student at Mälardalen University and part of the INNOFACTURE Research School since September 2012. He has also been employed as a maintenance engineer at Volvo Group Trucks Operation. The area of his research has been relied on development and implementation of condition based maintenance in the manufacturing industry. The results of his studies are published in the form of journal and conference papers. Ali received his M.Sc. from Mälardalen University in the area of Product and Process Development – Production and Logistics and his B.Sc. from Tehran Azad University in Mechanical Engineering. His background includes work as a mechanical and maintenance engineer in manufacturing industries.

Anders_Paulsen_Rolls_Royce_Marine
14:00
Intelligent Service

Anders Paulsen
Head of Research & Technology Intelligent Asset Management
Rolls-Royce

Matti_Laakso_KONE_Corporation
14:30
Challenges in modeling elevators for predictive maintenance

I present the unique challenge that the variety of different elevator makes, models, and types present to a company that provides predictive maintenance to all of them.

Learning points:
- Predictive maintenance of assets that vary a lot in their behavior presents an interesting challenge
- Asset behavior can be homogenized by a careful feature selection

Matti Laakso
Condition Monitoring Expert
KONE Corporation

Matti Laakso joined KONE in 2014. From the start he has been part of a project to utilize sensor data in the predictive maintenance of elevators. His expertise is in the overall sensor data pipeline from physical sensors and edge processing of sensor data to the generation of actionable insights.

Matti got his PhD in engineering physics in 2012 from Aalto University, Finland, and worked as a university research fellow in RWTH Aachen, Germany. He has written more than ten scientific publications.

Umid_Akhmedov_Orsted
15:00
Predictive maintenance use cases from the Energy sector

In this session we’ll discuss some use cases from an energy company that is taking advantage of predictive analytics to make the world greener.

Key takeaways:
Align with the business strategy
Build a solid data backbone
Formalize the process

Umid Akhmedov
Head of Advanced Analytics
Ørsted A/S

Umid Akhmedov holds a MSc degree in Finance from Aarhus University. He comes with extensive experience of building data driven solutions from financial and energy sectors. His team of data engineers and data scientists is responsible for supporting Ørsted’s initiatives in extracting value form data assets.

15:30
Coffee and networking - Peer-to-Peer meetings
Rerngvit_Yanggratoke_Combient_AB_
Renato_Silva_Neves_SKF_Sverige_AB
16:00
Automation of maintenance prediction for rotating assets using infrequent vibration measurements

Combient is a joint venture with a mission to accelerate digital transformation within the companies participating in our federated collaboration platform, with companies representing some of the largest traditional enterprises in Sweden and Finland. A significant part of this work has involved solving advanced analytics projects related to predictive maintenance. In this session, we will share challenges, methods and preliminary results from an ongoing project that Combient is carrying out together with SKF. We will describe a machine learning approach for determining the health state of rotating systems. The results are based on vibration data collected from 30,000 machines since 2001.

Learning points:
- Key challenges with building models for real-world data
- What can different industries learn from each other?

Rerngvit Yanggratok
Data scientist
Combient AB

Rerngvit Yanggratoke is currently working as a data scientist at Combient (www.combient.com), a joint venture owned by several global enterprises from Sweden and Finland, e.g., SAAB, Electrolux, LKAB, SKF, and Ericsson. His educational background is a Ph.D. degree in the area of applying data science for optimizing operations and management in data centers from KTH Royal Institute of Technology in Stockholm, Sweden. He has published over 20 scientific articles in international peer- reviewed journals and conferences. He received his MSc in Security and Mobile Computing from Aalto University, Finland and KTH, Sweden. He received his BSc degree in Computer Engineering from Chulalongkorn University, Bangkok, Thailand. His current interests are industrial advanced analytics, deep learning for natural language processing, and management of large distributed systems.

Renato Silva Neves
Manager Advanced Analytics and Visualization
SKF Sverige AB

Renato works with asset monitoring services, industrial maintenance and reliability in high sized companies for more than 14 years. He has a degree in Mechanical engineering and MBA in project management, solid experience in managing projects and people, digitalization and analytics solutions, maintenance services, fluency in the English language, intermediate level in Spanish and a Green Belt Lean Six Sigma certification. Currently an Engineering Coordinator at SKF Brazil, responsible for the management of four different areas and 22 collaborators.

Mikael_Miglis_ABB
16:30
The algorithm is never the problem -yet!

This talk is a short story about how ABB went from selling products to collaborating services. The business model is the key to success. In this talk I will explain how a Collaborative journey in digital transformation could eventually lead us so far that we start questioning our algorithms.

Key Takeways:

• Give an example of how advanced analytics most successfully can be delivered
• What impact does organizational structures have on our development?
• What can I do as a manager to enable a digital transformation?

Mikael Miglis
Collaborative Operations Manager & Product Manager - Advanced Series
ABB

I have been working with Service Sales for the last 8 years, including front end sales, Account Management, Product development and now as operations manager for the center from where we deliver our digital solutions.
I am an engineer (M.Sc. Mechanical Engineering) but with a strong focus on business. My biggest interest right now is in the development of business models for digital solutions.

Andreas_Stjernudde_SJAB
17:00
SJ goes Digital: The journey towards predictive maintenance

How to transform a company from mainly doing corrective and preventive maintenance, towards predictive maintenance. With different conditions applying to the assets and limited influence over infrastructure.

Learning points:
- Cooperation with external organizations
- Use of remote diagnostics
- Using IoT for PdM purposes

Andreas Stjernudde
Project manager
SJ AB

Andreas Stjernudde has been a maintenance analyst at SJ since the end of 2016 with the object of optimizing maintenance plans and increasing reliability. As of 2017 Andreas was assigned as project manager for the digitalization of SJ’s rolling stock, which is a part of the SJ Digital program. Andreas responsibilities as project manager are to coordinate different digitalization related projects to work towards a common goal. Andreas has a master’s degree in Industrial Management and has during his career managed projects, primarily related to transformation and organization.

17:30
Chairman´s Closing Remarks
17:50
Networking cocktail
George_Buckbee_Mesto
11:00
IIoT for Process Control (practical talk on what to measure, who to report it to)

Process Control Systems are uniquely positioned as one of the first industrial systems that can leverage the IIoT. Control systems are, by their very nature, already gathering and historizing massive quantities of data in real-time. Further, these systems typically have connectivity to office networks, intranet, and, in some cases, to the internet. Much of the talk about IIoT has been equipment-related, with monitoring of machines, turbines, compressors, and other large equipment. This paper addresses the routine monitoring of industrial control systems themselves. This includes monitoring of the performance of not only basic equipment, such as instrumentation and valves, but also monitoring of control loops, control strategies, and process results.

This paper will show practical examples of using IIoT principles to monitor thousands of control loops remotely. The paper will cover practical issues of IIoT, such as data access, security, filtering, and especially how to layer “knowledge filters” to provide intelligent, targeted information to many different types of users. Examples will also show how the resulting reports and analytics can be used to drive business results.

George Buckbee
Head of Performance Solutions
Mesto

George Buckbee, P.E. is an ISA Fellow, author of several process control books, and is currently Head of Performance Solutions, featuring Expertune family of products and services, at Metso. An experienced instructor, George has over 25 years of practical experience improving process performance in a wide array of process industries, including Oil & Gas, Pulp & Paper, Pharmaceuticals, and Consumer Products. George holds a B.S. in Chemical Engineering from Washington University, and an M.S. in Chemical Engineering from the University of California, Santa Barbara.

Marty_Cochrane_Arundo_Analytics
11:30
Edge Analytics & Data Lineage

Edge computing is the hot topic in the IIOT space at the moment and daily we are seeing exciting new examples of the use of edge in this space. Trusting where your sensor data is coming from and how it's been manipulated along the way is something that's still a challenge. Join me as I talk through technical examples of how this can be solved giving subscribers to your data clear transparency of where it has come from and how it's been manipulated along the way.

Learning points:
- Transparent data lineage from the edge
- Examples of edge applications
- Machine learning models on the edge
- Blockchain technology on the edge

Marty Cochrane
VP Solution Architecture EMEA
Arundo Analytics

Marty Cochrane is a software developer that specialises in developing software for the power industry. Working on the ground in 1960's coal fired power stations in Ireland all the way to the top of wind turbines on islands in the north of Norway. With a mechanical engineering background Marty strives to write software and control systems that optimises the running of any asset with the smart use of sensors in any heavy asset industry. Today in Arundo he is the director of Solution Architecture and loves getting his hands dirty with control systems and smart analytics on the edge.

Rado_Kotorov_Information_Builders
12:00
Industrial IOT - maintaining the machines

The 4th Industrial revolutions is all about data – using data as an asset and managing assets with data. The manufacturing sector is significantly impacted by this trend as most machines and processes embed sensors that collect vast amounts of data. Companies that leverage this data to optimize performance, maintain machines and even extend the lifecycle of machines reap significant benefits. This has lead to the emergence of new business models such as PAS (products as a service). In this presentation you will learn how to leverage data management and BI to get more value from your equipment.

Rado Kotorov
CIO
Information Builders

Dr. Rado Kotorov works with both the business intelligence (BI) and the iWay product divisions to provide thought leadership, analyze market and technology trends, develop innovative product roadmaps, and create rich programs to drive adoption of BI, analytic, data integrity, and integration technologies. He strives to make BI and business analytics more accessible, intuitive, and collaborative through the adoption of innovative Web 2.0, advanced visualization, predictive modeling, search, and mobile technologies.

12:30
Networking Lunch
Christian_Rasmussen_Grundfos
Signe_Horn_Thomsen_Grundfos
13:30
Clear expectations about data quality – the foundation for measuring and managing data

Crappy data is hindering swift delivery of analytics insight and we spend too much time cleaning up. Let’s start measure and manage.

Learning points:
- How data quality affect feasibility of a great opportunity
- A practical way to measure data quality in three dimensions
- Producing data is harder than consuming data
- How to help the data producer become better

Christian Rasmussen
Senior Manager, Data Analytics
Grundfos

Christian has worked with technology development, technology management and frontend innovation for the past 18 years. In 2017 he took up the challenge to build a Data Analytics capability for new digital offerings in Grundfos.I have always been a strong believer of more impact through cross functional collaboration. This is definitely the case working with data. Says Christian Christian holds a MSc from the Technical University of Denmark.

Signe Horn Thomsen
Data Analyst
Grundfos

Signe holds a Master's degree in IT, Communication and Organization from Aarhus University. In February 2018 she joined the Data Analytics team in Grundfos and is now working as a Data Analyst with focus on data quality. Signe is developing an assessment method for measuring the quality of data."The goal with this method is to ensure good data quality and thereby deliver valuable and trustworthy data analytics" says Signe.

Mark_Jaxion_Vestas
14:00
Implementation of IoT and Leveraging Machine Learning for data cleansing

Session Description: As Vestas begins the journey towards Industry 4.0 new challenges and obstacles arise. This session will explore how Vestas is beginning to use machine learning to overcome some of these challenges with legacy systems, poor master data, and the difficultly with digitalizing unstructured documentation. In addition, the session will cover what activities are currently underway at Vestas to ensure the successful implementation of the IoT project roadmap and our vision for the future.

Key Takeaways:
- Machine learning is a bedrock of data quality in the future
- Unstructured documentation comprehension is a key element in building a digital twin
- A strong data foundation will ensure harvest of full value from IoT Implementation

Mark Jaxion
IoT Lead and Industrialization 4.0
Vestas
Mark Jaxion is a Senior Specialist at Vestas Wind Systems. He is responsible for the IoT and Industry 4.0 roadmap for Industrialization within the Technology and Development area within Vestas, and has over 12 years working on deployment, implementation, and optimizations of ERP and PLM systems. Previously, Mark has worked on modelling and optimize supply chain, production operations and inventory planning.

Ashutosh_Kumar_Karsten_Moholt
14:30
Innovation in service and maintenance industry using predictive analytics: Practical experience of a service and maintenance partner

Karsten Moholt is one of the largest workshops in the Nordics for service, maintenance, condition monitoring and lifetime extension of electromechanical machines.
In this session, Ashutosh Kumar will talk about how Karsten Moholt is using data and predictive analytics in the era of digitalization to provide predictive maintenance (PdM) solutions. He will discuss about the changing maintenance strategies, their effects in the maintenance industry, new challenges and how Karsten Moholt is adapting with the new business needs.

Key takeaways:
- Innovation and Digitalisation enabling PdM in maintenance industry
- Traditional Condition monitoring and Predictive maintenance: Advantages and Challenges in both approaches
- How Karsten Moholt has always adapted with new business needs and new technologies.
- Case study of PdM in asset heavy industry


Ashutosh Kumar
Project Manager
Karsten Moholt A/S

Ashutosh is a Project manager for predictive maintenance (PdM) solutions at Karsten Moholt AS since August 2016. Currently he is leading pilot projects in PdM and innovative sensor technologies. He holds a Masters degree in RAMS (Reliability, Maintainability, Availability and Safety) from NTNU, Trondheim and has almost five years of industry experience in reliability and maintenance solutions and process automation in asset heavy industries. Prior to NTNU, he has worked in ABB India and Norway with Engineering and Commissioning of Industrial Automation Systems with clients namely Statoil and TATA Steel.

Bjarke_Osmundsen_Danfoss
15:00
Supporting Digital Transformation Through Data and Analytics

Lessons learned from establishing Data Analytics initiative in Danfoss leveraging advanced analytics techniques as well data mining and visualization for optimization and innovation.

Learning points:
- Meeting your stakeholders at eye level: Power of the 3 C's Concepts, Capabilities, Culture
- Fail Fast, be flexible and iterate
- Presentation of use cases with applied data analytics and mining techniques for both internal and external stakeholders

Bjarke Osmundsen
Data Analyst
Danfoss

Is currently driving the development and consolidation of data analytics projects in Danfoss and have more than five years of experience with applying data mining and visual analytics for innovation and optimization. The ability to understand business context and user perspectives has been key in creating value with data analytics in Danfoss. Bjarke is therefore driving business development with a focus on delivering flexible solutions that unlock data-driven insights.

15:30
Coffee and networking - Peer-to-Peer meetings
Lokukaluge_Prasad_Perera_UiT_The_Arctic_University_of_Norway
16:00
Reverse Engineering Approach for System Condition Monitoring under Big Data and Advanced Data Analytics

A novel mathematical framework to support condition monitoring and condition based maintenance is presented in this study. The framework consists of a data flow path, i.e. from Industrial IoT (i.e. with Big Data) to advanced data analytics with digital models and that can be a part of industrial data handling processes. The digital models are derived from ship performance and navigation data sets and a combination of such models facilitates towards proposed data analytics. Since the respective data sets are used to derive these analytics, that can be a good representation of the respective systems under different modeling levels. Hence, this mathematical framework is also categorized as a reverse engineering approach. Furthermore, a data anomaly detection and recover procedure associated with the same framework to improve the respective data quality is also described in this study.

Learning points:
- Utilization in big data sets for condition monitoring and condition based maintenance
- Reverse engineering of systems up to component levels from big data
- Advanced data analytics with digital models for conditions monitoring
- Data anomaly detection and recovery from data analytics
- Visual analytics towards system health conditions

Lokukaluge Prasad Perera
Associate Professor
UiT The Arctic University of Norway

L. P. Perera received the BSc (1999) and MSc (2001) degrees in Mechanical Engineering and Systems & Controls from the Oklahoma State University, USA and the PhD (2012) degree in Naval Architecture and Marine Engineering from the Technical University of Lisbon, Portugal. Currently, he is an Associate Professor at the Department of Engineering and Safety, UiT The Arctic University of Norway, Norway. His research experience includes the SINTEF Ocean (former MARINTEK) (2012-2017), Norway, Centre for Marine Technology and Engineering (2008-2012), Portugal and the Advanced Technology Research Center (1998-2001), USA. His academic experience includes the Naval & Maritime Academy (2005-2008), Sri Lanka and the Ocean University of Sri Lanka (2003-2005), Sri Lanka. Furthermore, Dr. Perera was a visiting lecture (2001-2005) for several academic institutes in Sri Lanka: University of Ruhuna, University of Moratuwa, Open University of Sri Lanka, Colombo International Nautical & Engineering College. His industrial experience includes Wartsila Finland, Finland (2012-2014). Dr. Perera's research interests include Maritime and Offshore Systems & Controls, Instrumentation, Data Analytics, Machine Learning & Artificial Intelligence, Autonomous Navigation, Intelligent Guidance & Decision Support, Condition Monitoring & Condition based Maintenance, Energy Efficiency & Emission Control.

Jarl_S_Magnusson_DNV_GL
16:30
DNVGL Predictive Maintenance Examples

Presenting the importance of data management and data quality in order to capture the right data, to adapt (transform and integrate) data and use it for advanced predictive maintenance analytics.

Learning points:
- Do we underestimate the need for data management and data quality?
- Profiling and Rules Libraries
- What is needed for continuous monitoring?
- Presenting some DNVGL and Customer examples from predictive maintenance

Jarl S. Magnusson
Principal Consultant - Information Risk Management Data Management Competency Centre (DMCC)
DNV GL

12:30
Networking Lunch

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Speakers

Speakers are what make events stand out. Maintenance Analytics Summit is bringing the most innovative minds, practitioners, experts and thinkers on two stages to inspire and present new innovative data-driven approaches to minimise asset downtime and improve service reliability.

Christian_Rasmussen_Grundfos_maintenanceanalyticssummit2018
Christian Rasmussen
Grundfos
Signe_Horn_Thomsen_Grundfos_maintenanceanalyticssummit2018
Signe Horn Thomsen
Grundfos
Jarl_S_Magnusson_DNV_GL_maintenanceanalyticssummit2018
Jarl S. Magnusson
DNV GL
Ali_Rastegari_VolvoGTO_maintenanceanalyticssummit2018
Ali Rastegari
Volvo GTO
Amer_Mohammed_Stena_Line_maintenanceanalyticssummit2018
Amer Mohammed
Stena Line
Peter_Loof_Health_Orsted_maintenanceanalyticssummit2018
Peter Loof Helth
Ørsted
Andreas_Stjernudde_SJ_AB_maintenanceanalyticssummit2018
Andreas Stjernudde
SJ AB
Anders_Paulsen_Rolls_Royce_Marine_maintenanceanalyticssummit2018
Anders Paulsen
Rolls-Royce
Mikael_Miglis_ABB_maintenanceanalyticssummit2018
Mikael Miglis
ABB
Lokukaluge_Prasad_Perera_maintenanceanalyticssummit2018
Lokukaluge Prasad Perera
UiT The Arctic University of Norway
Matti_Laakso_KONE_Corporation__maintenanceanalyticssummit2018
Matti Laakso
KONE Corporation
Rerngvit_Yanggratoke_Combient_AB_maintenanceanalyticssummit2018
Rerngvit Yanggratoke
Combient AB
Bjarke_Osmundsen_Danfoss_maintenanceanalyticssummit2018
Bjarke Osmundsen
Danfoss
Ashutosh_Kumar_Karsten_Moholt_ maintenanceanalyticssummit2018
Ashutosh Kumar
Karsten Moholt A/S
Mark_Jaxion_ Vestas_maintenanceanalyticssummit2018
Mark Jaxion
Vestas
Martin_Lundqvist_ maintenanceanalyticssummit2018
Martin Lundqvist
Arundo Analytics
Jake_Bouma_maintenanceanalyticssummit2018
Jake Bouma
Arundo Analytics
Kieran_Notter_ServiceMax_maintenanceanalyticssummit2018
Kieran Notter
ServiceMax
Marty_Cochrane_Arundo_Analytics_maintenanceanalyticssummit2018
Marty Cochrane
Arundo Analytics
Joseph_Morelos_Lloyds_Register_maintenanceanalyticssummit2018
Joseph Morelos
Lloyd’s Register
Umid_Akhmedov_Orsted_maintenanceanalyticssummit2018
Umid Akhmedov
Ørsted A/S
Renato_Silva_Neves_SKF_Sverige_AB_maintenanceanalyticssummit2018
Renato Silva Neves
SKF Sverige AB
George_Buckbee_Mesto_maintenanceanalyticssummit2018
George Buckbee
Metso
Rado_Kotorov_Information_Builders_maintenanceanalyticssummit2018
Rado Kotorov
Information Builders
Diego Galar LTU maintenanceanalyticssummit2018
Diego Galar
LTU